Fuzzy Cluster Analysis : A New Method to Predict Future Cardiac Events in Patients With Positive Stress Tests

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Several studies have shown that combining the change in the ST-segment with another exercise variable improves the predictive value of stress testing. However, no method has been able to combine many stress test variables with the ST-segment change simultaneously and help the clinician better predict future cardiac events. Fuzzy Cluster Analysis(FCA)was used to combine 5 stress test variables with ST-segment deviation to classify each of 232 positive outpatient stress tests as mildly, moderately, or severely abnormal. Cardiac events were recorded in these 3 patient groups up to 96 months(mean 65 months)after the stress tests. Coronary angiography was performed on 159 of these patients within 1 month of their stress tests. FCA better separated the 3 event-free survival curves than classifying the stress tests by three ST-segment(0.5-1.5mm, 2-2.5mm, >3mm)groups(p<0.05). At 2 years, 90% of the FCA mild group were compared with 70% for the 0.5-1.5mm group(p<0.01). Moderate and severe tests by FCA separated patients with an intermediate from those with a poor prognosis while the 2-2.5mm and 3mm or more ST-segment curves did not(p<0.05). FCA showed overall better correlation with coronary score(r=0.71)than did the graded ST-segment groups(r=0.48). FCA predicted both mild and high-grade(triple-vessel and left main)coronary disease better than ST-segment alone. Thus FCA better predicts future cardiac events in patients with positive stress tests than the ST-segment alone. This combined with its usefulness in predicting the extent of coronary disease provides the basis of a clinical strategy for managing patients with positive stress tests.
社団法人日本循環器学会の論文
1998-09-20

Fuzzy Cluster Analysis : A New Method to Predict Future Cardiac Events in Patients With Positive Stress Tests

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